{"as_of":"2026-08-09T22:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5aa143c94f93a291f5e951a1af09874514e71d53fe4ff8c2034e825acacbdb28","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T10:20:20.991380Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.07233","last_updated":"2025-05-16T02:47:07Z","snapshot_observed_at":"2026-08-07T15:47:59.868013Z","submitted_at":"2025-05-12T05:19:01Z","title":"DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.07233","snapshot_observed_at":"2026-08-04T10:20:20.991380Z","title":"Richard S Sutton, Andrew G Barto, and 1 others","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2510.10448","last_updated":"2026-06-06T05:24:14Z","snapshot_observed_at":"2026-08-07T11:41:38.195425Z","submitted_at":"2025-10-12T05:00:05Z","title":"RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-04T10:20:20.991380Z"},"links":{"cited_paper":"/paper/2505.07233","citing_paper":"/paper/2510.10448"},"observation_digest":"sha256:1df0b8927de9ae6f9a1f963746bd9984708fc956cb962f64d84c9d563875b6a5","observation_id":"5f25fbd1-4f95-44fc-8cd2-0267dda19230","resolution":{"observed_at":"2026-08-04T10:20:20.991380Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.07233","last_updated":"2025-05-16T02:47:07Z","snapshot_observed_at":"2026-08-07T15:47:59.868013Z","submitted_at":"2025-05-12T05:19:01Z","title":"DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.07233","snapshot_observed_at":"2026-07-13T13:59:01.287449Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2604.02091","last_updated":"2026-07-02T17:08:51Z","snapshot_observed_at":"2026-08-09T18:07:23.071685Z","submitted_at":"2026-04-02T14:19:47Z","title":"Optimizing RAG Rerankers with LLM Feedback via Reinforcement Learning","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-07-13T13:59:01.287449Z"},"links":{"cited_paper":"/paper/2505.07233","citing_paper":"/paper/2604.02091"},"observation_digest":"sha256:244b6eb4a35310271da6d8fbca4ba5a047ff4e1293065ad4438de9e15cf28901","observation_id":"c5c6cba6-58a2-4529-a767-ee34a853a36c","resolution":{"observed_at":"2026-07-13T13:59:01.287449Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.07233","last_updated":"2025-05-16T02:47:07Z","snapshot_observed_at":"2026-08-07T15:47:59.868013Z","submitted_at":"2025-05-12T05:19:01Z","title":"DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation","version":2},"cited_work":{"arxiv_id":"2505.07233","doi":"10.48550/arxiv.2505.07233","metadata_source":"arxiv_reference","pith_arxiv_id":"2505.07233","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"ArXiv.org","work_id":"66d799a0-f8c0-4225-a0f5-5a72d36dfe6c","year":2025},"citing_paper":{"arxiv_id":"2605.14236","last_updated":"2026-05-15T17:58:25Z","snapshot_observed_at":"2026-08-03T09:39:32.296200Z","submitted_at":"2026-05-14T01:03:53Z","title":"Active Learners as Efficient PRP Rerankers","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-05-15T01:43:10.436537Z"},"links":{"cited_paper":"/paper/2505.07233","citing_paper":"/paper/2605.14236"},"observation_digest":"sha256:035e754bc2e1665802427bd22f5fe5b5f5d883ba00a747d73ffec0f0626402aa","observation_id":"63a72e2d-e962-4c9c-ab36-e4f399c4fd73","resolution":{"observed_at":"2026-05-15T01:43:27.227839Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.07233","last_updated":"2025-05-16T02:47:07Z","snapshot_observed_at":"2026-08-07T15:47:59.868013Z","submitted_at":"2025-05-12T05:19:01Z","title":"DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation","version":2},"cited_work":{"arxiv_id":"2505.07233","doi":"10.48550/arxiv.2505.07233","metadata_source":"arxiv_reference","pith_arxiv_id":"2505.07233","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"ArXiv.org","work_id":"66d799a0-f8c0-4225-a0f5-5a72d36dfe6c","year":2025},"citing_paper":{"arxiv_id":"2605.14236","last_updated":"2026-05-15T17:58:25Z","snapshot_observed_at":"2026-08-03T09:39:32.296200Z","submitted_at":"2026-05-14T01:03:53Z","title":"Active Learners as Efficient PRP Rerankers","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-05-20T21:07:32.652880Z"},"links":{"cited_paper":"/paper/2505.07233","citing_paper":"/paper/2605.14236"},"observation_digest":"sha256:5cb87529055d8dddc02ee58acfe3d91b14115a2ad33675d71914b8476ae80ee0","observation_id":"afe64bb5-0998-41c4-b816-5a7138231377","resolution":{"observed_at":"2026-05-20T21:09:02.442786Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2505.07233/citation-record","integrity":"/paper/2505.07233/integrity","json":"/paper/2505.07233/citation-record.json","paper":"/paper/2505.07233"},"outbound":[],"paper":{"arxiv_id":"2505.07233","last_updated":"2025-05-16T02:47:07Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T15:47:59.868013Z","submitted_at":"2025-05-12T05:19:01Z","title":"DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2505.07233."}